String Algorithms and Pattern Matching Questions

Covers algorithmic techniques and practical skills for solving string problems and pattern matching tasks. Core algorithm knowledge includes substring search and pattern matching algorithms such as Knuth Morris Pratt, Rabin Karp, Boyer Moore, Z algorithm, Aho Corasick for multiple pattern matching, and rolling hash methods. Data structures and suffix structures are important, including tries, suffix arrays, suffix trees, and suffix automata, together with longest common prefix arrays and related construction techniques. Also includes dynamic programming approaches for string problems such as edit distance and longest common subsequence, palindrome and anagram detection methods, and regular expression concepts and engine behavior. Emphasizes algorithmic complexity analysis, time and space trade offs, memory and streaming constraints, and optimization strategies for very long inputs and high throughput text processing. Practical considerations include parsing and string manipulation idioms in common languages, Unicode and character encoding issues, edge case handling, test case design for strings, and real world applications such as log analysis, text search, and data transformation.

HardTechnical

84 practiced

Implement a suffix automaton (SAM) construction in C++ for a string s and use it to compute the number of distinct substrings of s. Also describe how to use SAM to compute the longest common substring between s and another string t. Explain states, transitions, links, and complexity.

HardSystem Design

92 practiced

Design a scalable system to support fast substring and regex searches over petabytes of logs with high ingestion rate and low query latency. Discuss indexing strategies (inverted index, n-gram indexing, suffix-based), sharding, compression, near-real-time ingestion, query routing, and how approximate matching can be supported.

EasyTechnical

47 practiced

Explain greedy vs lazy quantifiers in regular expressions and give a concrete example where greedy matching produces a different result from lazy matching. Define catastrophic backtracking, show a regex example that can trigger it, and describe how to mitigate the issue.

HardTechnical

57 practiced

Given k input strings with total length N, describe an algorithm using a generalized suffix array plus LCP array to find the longest substring common to all k strings. Outline building the generalized SA, annotating suffixes by source string, and scanning LCP intervals to find the maximal common substring across all k origins.

HardSystem Design

62 practiced

Design an incremental autocomplete (typeahead) service for a global user base: low latency per keystroke, millions of terms, frequent updates, and ranking by popularity. Compare approaches: trie with cached top-k per node, suffix array, and inverted index. Discuss update pipelines, memory budgets, sharding, and ranking/pagination strategies.

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